code: def test_fabric_dataloader_device_placement(
      src_device_str, dest_device_str
  ):
      """Test that the FabricDataLoader moves data to the device in its iterator."""
      src_device = torch.device(src_device_str)
      dest_device = torch.device(dest_device_str)
  
      sample0 = torch.tensor(0, device=src_device)
      sample1 = torch.tensor(1, device=src_device)
      sample2 = {"data": torch.tensor(2, device=src_device)}
      sample3 = {"data": torch.tensor(3, device=src_device)}
      dataloader = DataLoader(
          [sample0, sample1, sample2, sample3], batch_size=2
      )
      fabric_dataloader = _FabricDataLoader(
          dataloader=dataloader, device=dest_device
      )
      iterator = iter(fabric_dataloader)
  
      batch0 = next(iterator)
      assert torch.equal(
          batch0, torch.tensor([0, 1], device=dest_device)
      )
  
      batch1 = next(iterator)
      assert torch.equal(
          batch1["data"], torch.tensor([2, 3], device=dest_device)
      )
  
imports: from unittest import mock
  from unittest.mock import Mock, call
  import pytest
  import torch
  from lightning.fabric.fabric import Fabric
  from lightning.fabric.plugins import Precision
  from lightning.fabric.utilities.device_dtype_mixin import _DeviceDtypeModuleMixin
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_1
  from lightning.fabric.wrappers import _FabricDataLoader, _FabricModule, _FabricOptimizer, _unwrap_objects, is_wrapped
  from torch.utils.data import BatchSampler, DistributedSampler
  from torch.utils.data.dataloader import DataLoader
  from tests_fabric.helpers.runif import RunIf
label_desc: Use image node_id 9 for calling a global function with example usage: test_fabric_dataloader_device_placement(src_device_str, dest_device_str) without return types